Overview

Dataset statistics

Number of variables7
Number of observations34
Missing cells36
Missing cells (%)15.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory59.8 B

Variable types

Text4
Categorical3

Dataset

Description대구광역시 동구 관내에 신고된 폐기물처리업 현황입니다. 신고자 상호, 위치, 연락처, 업종, 처리폐기물종류 등의 항목을 포함합니다.
Author대구광역시 동구
URLhttps://www.data.go.kr/data/15035316/fileData.do

Alerts

관할관청 has constant value ""Constant
업종 is highly overall correlated with 처분업종류High correlation
처분업종류 is highly overall correlated with 업종High correlation
처리시설소재지 has 21 (61.8%) missing valuesMissing
연락처 has 15 (44.1%) missing valuesMissing

Reproduction

Analysis started2024-03-15 01:42:32.229268
Analysis finished2024-03-15 01:42:33.759818
Duration1.53 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호
Text

Distinct33
Distinct (%)97.1%
Missing0
Missing (%)0.0%
Memory size400.0 B
2024-03-15T10:42:34.343434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length4.9705882
Min length2

Characters and Unicode

Total characters169
Distinct characters83
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)94.1%

Sample

1st row대동수지공업사
2nd row자유보호작업장
3rd row신성비철산업
4th row신성상사
5th row대한민국상이군경회 대구사업소
ValueCountFrequency (%)
㈜유창알앤씨 2
 
5.7%
가온유통 1
 
2.9%
195유통 1
 
2.9%
새봄무역 1
 
2.9%
대창상회 1
 
2.9%
팔공유통 1
 
2.9%
대구제일유지 1
 
2.9%
파란 1
 
2.9%
에스지유통 1
 
2.9%
송백농장 1
 
2.9%
Other values (24) 24
68.6%
2024-03-15T10:42:35.620593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
유 12
 
7.1%
통 7
 
4.1%
㈜ 6
 
3.6%
대 6
 
3.6%
지 6
 
3.6%
업 5
 
3.0%
동 5
 
3.0%
사 5
 
3.0%
상 5
 
3.0%
일 4
 
2.4%
Other values (73) 108
63.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 159
94.1%
Other Symbol 6
 
3.6%
Decimal Number 3
 
1.8%
Space Separator 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
유 12
 
7.5%
통 7
 
4.4%
대 6
 
3.8%
지 6
 
3.8%
업 5
 
3.1%
동 5
 
3.1%
사 5
 
3.1%
상 5
 
3.1%
일 4
 
2.5%
자 4
 
2.5%
Other values (68) 100
62.9%
Decimal Number
ValueCountFrequency (%)
1 1
33.3%
9 1
33.3%
5 1
33.3%
Other Symbol
ValueCountFrequency (%)
㈜ 6
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 165
97.6%
Common 4
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
유 12
 
7.3%
통 7
 
4.2%
㈜ 6
 
3.6%
대 6
 
3.6%
지 6
 
3.6%
업 5
 
3.0%
동 5
 
3.0%
사 5
 
3.0%
상 5
 
3.0%
일 4
 
2.4%
Other values (69) 104
63.0%
Common
ValueCountFrequency (%)
1 1
25.0%
9 1
25.0%
5 1
25.0%
1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 159
94.1%
None 6
 
3.6%
ASCII 4
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
유 12
 
7.5%
통 7
 
4.4%
대 6
 
3.8%
지 6
 
3.8%
업 5
 
3.1%
동 5
 
3.1%
사 5
 
3.1%
상 5
 
3.1%
일 4
 
2.5%
자 4
 
2.5%
Other values (68) 100
62.9%
None
ValueCountFrequency (%)
㈜ 6
100.0%
ASCII
ValueCountFrequency (%)
1 1
25.0%
9 1
25.0%
5 1
25.0%
1
25.0%

처리시설소재지
Text

MISSING 

Distinct12
Distinct (%)92.3%
Missing21
Missing (%)61.8%
Memory size400.0 B
2024-03-15T10:42:36.291027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length23
Mean length22.538462
Min length21

Characters and Unicode

Total characters293
Distinct characters41
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)84.6%

Sample

1st row대구광역시 동구 안심로 55길 4(동호동)
2nd row대구광역시 동구 팔공산로 225(덕곡동)
3rd row대구광역시 동구 안심로 347(각산동)
4th row대구광역시 동구 안심로65길 14(각산동)
5th row대구광역시 동구 안심로65길 17(각산동)
ValueCountFrequency (%)
대구광역시 13
24.1%
동구 13
24.1%
안심로 3
 
5.6%
안심로65길 3
 
5.6%
공항로31길 2
 
3.7%
26(불로동 2
 
3.7%
33(용계동 1
 
1.9%
280 1
 
1.9%
공항로 1
 
1.9%
28-10(부동 1
 
1.9%
Other values (14) 14
25.9%
2024-03-15T10:42:37.329662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
41
 
14.0%
동 26
 
8.9%
구 26
 
8.9%
로 15
 
5.1%
대 13
 
4.4%
광 13
 
4.4%
역 13
 
4.4%
시 13
 
4.4%
) 12
 
4.1%
( 12
 
4.1%
Other values (31) 109
37.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 175
59.7%
Decimal Number 50
 
17.1%
Space Separator 41
 
14.0%
Close Punctuation 12
 
4.1%
Open Punctuation 12
 
4.1%
Dash Punctuation 2
 
0.7%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 26
14.9%
구 26
14.9%
로 15
8.6%
대 13
 
7.4%
광 13
 
7.4%
역 13
 
7.4%
시 13
 
7.4%
길 8
 
4.6%
안 7
 
4.0%
심 6
 
3.4%
Other values (16) 35
20.0%
Decimal Number
ValueCountFrequency (%)
2 8
16.0%
5 8
16.0%
1 7
14.0%
3 7
14.0%
6 6
12.0%
0 4
8.0%
8 4
8.0%
4 3
 
6.0%
7 2
 
4.0%
9 1
 
2.0%
Space Separator
ValueCountFrequency (%)
41
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 175
59.7%
Common 118
40.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 26
14.9%
구 26
14.9%
로 15
8.6%
대 13
 
7.4%
광 13
 
7.4%
역 13
 
7.4%
시 13
 
7.4%
길 8
 
4.6%
안 7
 
4.0%
심 6
 
3.4%
Other values (16) 35
20.0%
Common
ValueCountFrequency (%)
41
34.7%
) 12
 
10.2%
( 12
 
10.2%
2 8
 
6.8%
5 8
 
6.8%
1 7
 
5.9%
3 7
 
5.9%
6 6
 
5.1%
0 4
 
3.4%
8 4
 
3.4%
Other values (5) 9
 
7.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 175
59.7%
ASCII 118
40.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
41
34.7%
) 12
 
10.2%
( 12
 
10.2%
2 8
 
6.8%
5 8
 
6.8%
1 7
 
5.9%
3 7
 
5.9%
6 6
 
5.1%
0 4
 
3.4%
8 4
 
3.4%
Other values (5) 9
 
7.6%
Hangul
ValueCountFrequency (%)
동 26
14.9%
구 26
14.9%
로 15
8.6%
대 13
 
7.4%
광 13
 
7.4%
역 13
 
7.4%
시 13
 
7.4%
길 8
 
4.6%
안 7
 
4.0%
심 6
 
3.4%
Other values (16) 35
20.0%

연락처
Text

MISSING 

Distinct18
Distinct (%)94.7%
Missing15
Missing (%)44.1%
Memory size400.0 B
2024-03-15T10:42:38.027354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.052632
Min length12

Characters and Unicode

Total characters229
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)89.5%

Sample

1st row053-962-5758
2nd row053-986-3090
3rd row053-963-8877
4th row053-963-2233
5th row053-963-2235
ValueCountFrequency (%)
053-986-7113 2
 
10.5%
070-8235-2132 1
 
5.3%
053-962-5758 1
 
5.3%
053-353-8126 1
 
5.3%
053-986-4433 1
 
5.3%
053-965-9077 1
 
5.3%
053-964-4554 1
 
5.3%
053-944-7020 1
 
5.3%
053-964-4477 1
 
5.3%
053-964-6644 1
 
5.3%
Other values (8) 8
42.1%
2024-03-15T10:42:39.151222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 38
16.6%
3 36
15.7%
5 29
12.7%
0 26
11.4%
9 22
9.6%
6 18
7.9%
4 16
7.0%
2 14
 
6.1%
8 12
 
5.2%
7 12
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 191
83.4%
Dash Punctuation 38
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 36
18.8%
5 29
15.2%
0 26
13.6%
9 22
11.5%
6 18
9.4%
4 16
8.4%
2 14
 
7.3%
8 12
 
6.3%
7 12
 
6.3%
1 6
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 229
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 38
16.6%
3 36
15.7%
5 29
12.7%
0 26
11.4%
9 22
9.6%
6 18
7.9%
4 16
7.0%
2 14
 
6.1%
8 12
 
5.2%
7 12
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 229
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 38
16.6%
3 36
15.7%
5 29
12.7%
0 26
11.4%
9 22
9.6%
6 18
7.9%
4 16
7.0%
2 14
 
6.1%
8 12
 
5.2%
7 12
 
5.2%

업종
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size400.0 B
지정외 폐기물 수집운반업
22 
지정외 폐기물 처리업
11 
지정폐기물 수집운반업
 
1

Length

Max length13
Median length13
Mean length12.294118
Min length11

Unique

Unique1 ?
Unique (%)2.9%

Sample

1st row지정외 폐기물 처리업
2nd row지정외 폐기물 처리업
3rd row지정외 폐기물 처리업
4th row지정외 폐기물 처리업
5th row지정외 폐기물 처리업

Common Values

ValueCountFrequency (%)
지정외 폐기물 수집운반업 22
64.7%
지정외 폐기물 처리업 11
32.4%
지정폐기물 수집운반업 1
 
2.9%

Length

2024-03-15T10:42:39.398296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T10:42:39.802799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
지정외 33
32.7%
폐기물 33
32.7%
수집운반업 23
22.8%
처리업 11
 
10.9%
지정폐기물 1
 
1.0%

처분업종류
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size400.0 B
폐기물처리(수집운반)신고자
22 
종합재활용업
7 
폐기물처리(재활용)신고자
5 

Length

Max length14
Median length14
Mean length12.205882
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row종합재활용업
2nd row종합재활용업
3rd row종합재활용업
4th row종합재활용업
5th row종합재활용업

Common Values

ValueCountFrequency (%)
폐기물처리(수집운반)신고자 22
64.7%
종합재활용업 7
 
20.6%
폐기물처리(재활용)신고자 5
 
14.7%

Length

2024-03-15T10:42:40.103597image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T10:42:40.322701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐기물처리(수집운반)신고자 22
64.7%
종합재활용업 7
 
20.6%
폐기물처리(재활용)신고자 5
 
14.7%

처리폐기물종류
Text

Distinct18
Distinct (%)52.9%
Missing0
Missing (%)0.0%
Memory size400.0 B
2024-03-15T10:42:40.864723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length29
Mean length9
Min length3

Characters and Unicode

Total characters306
Distinct characters63
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)44.1%

Sample

1st row폐합성수지류
2nd row폐식용유
3rd row폐합성고무류(폐코팅롤)
4th row폐합성수지류(폐전선,폐통신케이블,고철)
5th row폐합성수지류(폐전선,폐통신케이블,폐모터,인쇄회로기관,고철,폐합성수지)
ValueCountFrequency (%)
폐의류 10
27.0%
폐식용유 8
21.6%
폐합성수지류(폐전선,폐통신케이블,고철 2
 
5.4%
가정용폐전기전자제품 2
 
5.4%
음식물류 2
 
5.4%
동물성잔재물 1
 
2.7%
폐합성수지류 1
 
2.7%
유지 1
 
2.7%
동물성 1
 
2.7%
영농폐기물(농약농기류 1
 
2.7%
Other values (8) 8
21.6%
2024-03-15T10:42:41.866139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
폐 50
 
16.3%
류 21
 
6.9%
, 16
 
5.2%
전 12
 
3.9%
성 10
 
3.3%
의 10
 
3.3%
( 10
 
3.3%
지 10
 
3.3%
용 10
 
3.3%
식 10
 
3.3%
Other values (53) 147
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 267
87.3%
Other Punctuation 16
 
5.2%
Open Punctuation 10
 
3.3%
Close Punctuation 10
 
3.3%
Space Separator 3
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
폐 50
18.7%
류 21
 
7.9%
전 12
 
4.5%
성 10
 
3.7%
의 10
 
3.7%
지 10
 
3.7%
용 10
 
3.7%
식 10
 
3.7%
유 9
 
3.4%
합 8
 
3.0%
Other values (49) 117
43.8%
Other Punctuation
ValueCountFrequency (%)
, 16
100.0%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 267
87.3%
Common 39
 
12.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
폐 50
18.7%
류 21
 
7.9%
전 12
 
4.5%
성 10
 
3.7%
의 10
 
3.7%
지 10
 
3.7%
용 10
 
3.7%
식 10
 
3.7%
유 9
 
3.4%
합 8
 
3.0%
Other values (49) 117
43.8%
Common
ValueCountFrequency (%)
, 16
41.0%
( 10
25.6%
) 10
25.6%
3
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 267
87.3%
ASCII 39
 
12.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
폐 50
18.7%
류 21
 
7.9%
전 12
 
4.5%
성 10
 
3.7%
의 10
 
3.7%
지 10
 
3.7%
용 10
 
3.7%
식 10
 
3.7%
유 9
 
3.4%
합 8
 
3.0%
Other values (49) 117
43.8%
ASCII
ValueCountFrequency (%)
, 16
41.0%
( 10
25.6%
) 10
25.6%
3
 
7.7%

관할관청
Categorical

CONSTANT 

Distinct1
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size400.0 B
대구광역시 동구청
34 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row대구광역시 동구청
2nd row대구광역시 동구청
3rd row대구광역시 동구청
4th row대구광역시 동구청
5th row대구광역시 동구청

Common Values

ValueCountFrequency (%)
대구광역시 동구청 34
100.0%

Length

2024-03-15T10:42:42.188577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T10:42:42.558399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대구광역시 34
50.0%
동구청 34
50.0%

Correlations

2024-03-15T10:42:42.750586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상호처리시설소재지연락처업종처분업종류처리폐기물종류
상호1.0001.0001.0001.0000.0000.000
처리시설소재지1.0001.0001.0001.0000.8640.870
연락처1.0001.0001.0001.0000.4890.899
업종1.0001.0001.0001.0000.9140.988
처분업종류0.0000.8640.4890.9141.0000.881
처리폐기물종류0.0000.8700.8990.9880.8811.000
2024-03-15T10:42:43.023892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종처분업종류
업종1.0000.641
처분업종류0.6411.000
2024-03-15T10:42:43.251288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종처분업종류
업종1.0000.641
처분업종류0.6411.000

Missing values

2024-03-15T10:42:32.818574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T10:42:33.291960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-03-15T10:42:33.626617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

상호처리시설소재지연락처업종처분업종류처리폐기물종류관할관청
0대동수지공업사대구광역시 동구 안심로 55길 4(동호동)053-962-5758지정외 폐기물 처리업종합재활용업폐합성수지류대구광역시 동구청
1자유보호작업장대구광역시 동구 팔공산로 225(덕곡동)053-986-3090지정외 폐기물 처리업종합재활용업폐식용유대구광역시 동구청
2신성비철산업대구광역시 동구 안심로 347(각산동)053-963-8877지정외 폐기물 처리업종합재활용업폐합성고무류(폐코팅롤)대구광역시 동구청
3신성상사대구광역시 동구 안심로65길 14(각산동)053-963-2233지정외 폐기물 처리업종합재활용업폐합성수지류(폐전선,폐통신케이블,고철)대구광역시 동구청
4대한민국상이군경회 대구사업소대구광역시 동구 안심로65길 17(각산동)053-963-2235지정외 폐기물 처리업종합재활용업폐합성수지류(폐전선,폐통신케이블,폐모터,인쇄회로기관,고철,폐합성수지)대구광역시 동구청
5경북재향군인회각산동지점대구광역시 동구 안심로65길 8(각산동)053-963-3408지정외 폐기물 처리업종합재활용업폐합성수지류(폐전선,폐통신케이블,고철)대구광역시 동구청
6㈜유창알앤씨대구광역시 동구 공항로31길 26(불로동)053-986-7113지정외 폐기물 처리업종합재활용업폐합성수지류(폐플라스틱,폐스티로폼)대구광역시 동구청
7㈜유창알앤씨대구광역시 동구 공항로31길 26(불로동)053-986-7113지정외 폐기물 처리업폐기물처리(재활용)신고자폐합성수지류(폐지,고철,폐타이어,폐가전제품,폐포장재)대구광역시 동구청
8아지매환경대구광역시 동구 신덕로2길 33(용계동)053-962-9844지정외 폐기물 처리업폐기물처리(재활용)신고자음식물류대구광역시 동구청
9동광<NA>053-965-9359지정외 폐기물 수집운반업폐기물처리(재활용)신고자폐식용유대구광역시 동구청
상호처리시설소재지연락처업종처분업종류처리폐기물종류관할관청
24디에스유통<NA><NA>지정외 폐기물 수집운반업폐기물처리(수집운반)신고자폐식용유대구광역시 동구청
25에스지유통<NA><NA>지정외 폐기물 수집운반업폐기물처리(수집운반)신고자폐식용유대구광역시 동구청
26클린유지<NA><NA>지정외 폐기물 수집운반업폐기물처리(수집운반)신고자폐식용유대구광역시 동구청
27가온유통<NA><NA>지정외 폐기물 수집운반업폐기물처리(수집운반)신고자폐식용유대구광역시 동구청
28대구제일유지<NA><NA>지정외 폐기물 수집운반업폐기물처리(수집운반)신고자동물성 유지대구광역시 동구청
29팔공유통<NA><NA>지정외 폐기물 수집운반업폐기물처리(수집운반)신고자폐의류대구광역시 동구청
30대창상회<NA><NA>지정외 폐기물 수집운반업폐기물처리(수집운반)신고자폐의류대구광역시 동구청
31새봄무역대구광역시 동구 옻골로 28-10(부동)<NA>지정외 폐기물 수집운반업폐기물처리(수집운반)신고자폐의류대구광역시 동구청
32195유통<NA><NA>지정외 폐기물 수집운반업폐기물처리(수집운반)신고자폐식용유대구광역시 동구청
33태영물류㈜대구광역시 동구 공항로 280, 501호053-952-7282지정외 폐기물 수집운반업폐기물처리(수집운반)신고자영농폐기물(폐비닐)대구광역시 동구청